Prof. Linda G. Shapiro Profile

Prof. Linda G. Shapiro

Associate Professor at Univ of Washington

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Publications (18)

Proceedings Article | 18 March 2019 Presentation + Paper

From patch-level to ROI-level deep feature representations for breast histopathology classification

Caner Mercan, Selim Aksoy, Ezgi Mercan, Linda Shapiro, Donald Weaver, Joann Elmore

Proceedings Volume 10956, 109560H (2019) https://doi.org/10.1117/12.2510665

KEYWORDS: Breast, Feature extraction, Diagnostics, Cancer, Pathology, Convolutional neural networks, Image classification, Image analysis

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Proceedings Article | 23 March 2016 Paper

Multi-instance multi-label learning for whole slide breast histopathology

Caner Mercan, Ezgi Mercan, Selim Aksoy, Linda Shapiro, Donald Weaver, Joann Elmore

Proceedings Volume 9791, 979108 (2016) https://doi.org/10.1117/12.2216458

KEYWORDS: Breast, Computer aided diagnosis and therapy, Image classification, Diagnostics, Pathology, Image analysis, Biopsy, Imaging technologies, Imaging systems, Computing systems, Zoom lenses, Cancer, Machine learning, Binary data, Feature extraction

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Digitization of full biopsy slides using the whole slide imaging technology has provided new opportunities for understanding the diagnostic process of pathologists and developing more accurate computer aided diagnosis systems. However, the whole slide images also provide two new challenges to image analysis algorithms. The first one is the need for simultaneous localization and classification of malignant areas in these large images, as different parts of the image may have different levels of diagnostic relevance. The second challenge is the uncertainty regarding the correspondence between the particular image areas and the diagnostic labels typically provided by the pathologists at the slide level. In this paper, we exploit a data set that consists of recorded actions of pathologists while they were interpreting whole slide images of breast biopsies to find solutions to these challenges. First, we extract candidate regions of interest (ROI) from the logs of pathologists' image screenings based on different actions corresponding to zoom events, panning motions, and fixations. Then, we model these ROIs using color and texture features. Next, we represent each slide as a bag of instances corresponding to the collection of candidate ROIs and a set of slide-level labels extracted from the forms that the pathologists filled out according to what they saw during their screenings. Finally, we build classifiers using five different multi-instance multi-label learning algorithms, and evaluate their performances under different learning and validation scenarios involving various combinations of data from three expert pathologists. Experiments that compared the slide-level predictions of the classifiers with the reference data showed average precision values up to 62% when the training and validation data came from the same individual pathologist's viewing logs, and an average precision of 64% was obtained when the candidate ROIs and the labels from all pathologists were combined for each slide.

Proceedings Article | 27 March 2009 Paper

R. Tungaraza, J. Guan, S. Rolfe, I. Atmosukarto, A. Poliakov, N. Kleinhans, E. Aylward, J. Ojemann, J. Brinkley, L. Shapiro

Proceedings Volume 7259, 72590E (2009) https://doi.org/10.1117/12.811357

KEYWORDS: Functional magnetic resonance imaging, Brain, 3D modeling, Brain mapping, Databases, 3D image processing, Feature extraction, Neuroimaging, Image retrieval, Facial recognition systems

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Proceedings Article | 27 March 2009 Paper

An independent component analysis based tool for exploring functional connections in the brain

S. Rolfe, L. Finney, R. Tungaraza, J. Guan, L. Shapiro, J. Brinkley, A. Poliakov, N. Kleinhans, E. Alyward

Proceedings Volume 7259, 725921 (2009) https://doi.org/10.1117/12.811648

KEYWORDS: Scanning probe microscopy, Brain, Brain mapping, Independent component analysis, Functional magnetic resonance imaging, Databases, Magnetic resonance imaging, Human-machine interfaces, Data modeling, Surgery

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Proceedings Article | 27 March 2009 Paper

Automatic 3D shape severity quantification and localization for deformational plagiocephaly

Indriyati Atmosukarto, Linda Shapiro, Michael Cunningham, Matthew Speltz

Proceedings Volume 7259, 725952 (2009) https://doi.org/10.1117/12.810871

KEYWORDS: Head, 3D modeling, Skull, Photography, Data acquisition, Shape analysis, 3D acquisition, Ear, Data processing, Nose

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Proceedings Article | 19 January 2009 Paper

A model of multimodal fusion for medical applications

S. Yang, I. Atmosukarto, J. Franklin, J. Brinkley, D. Suciu, L. Shapiro

Proceedings Volume 7255, 72550H (2009) https://doi.org/10.1117/12.805490

KEYWORDS: Distance measurement, Eye, Skull, Image retrieval, Databases, Human-machine interfaces, Biomedical optics, Functional magnetic resonance imaging, Image fusion, Medical imaging

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Proceedings Article | 18 March 2008 Paper

A new fringeline-tracking approach for color Doppler ultrasound imaging phase unwrapping

Ashraf Saad, Linda Shapiro

Proceedings Volume 6920, 69200G (2008) https://doi.org/10.1117/12.768304

KEYWORDS: Doppler effect, Ultrasonography, Phase shifts, Blood circulation, Algorithm development, Detection and tracking algorithms, In vivo imaging, In vitro testing, Data acquisition, Magnetic resonance imaging

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Color Doppler ultrasound imaging is a powerful non-invasive diagnostic tool for many clinical applications that involve examining the anatomy and hemodynamics of human blood vessels. These clinical applications include cardio-vascular diseases, obstetrics, and abdominal diseases. Since its commercial introduction in the early eighties, color Doppler ultrasound imaging has been used mainly as a qualitative tool with very little attempts to quantify its images. Many imaging artifacts hinder the quantification of the color Doppler images, the most important of which is the aliasing artifact that distorts the blood flow velocities measured by the color Doppler technique. In this work we will address the color Doppler aliasing problem and present a recovery methodology for the true flow velocities from the aliased ones. The problem is formulated as a 2D phase-unwrapping problem, which is a well-defined problem with solid theoretical foundations for other imaging domains, including synthetic aperture radar and magnetic resonance imaging. This paper documents the need for a phase unwrapping algorithm for use in color Doppler ultrasound image analysis. It describes a new phase-unwrapping algorithm that relies on the recently developed cutline detection approaches. The algorithm is novel in its use of heuristic information provided by the ultrasound imaging modality to guide the phase unwrapping process. Experiments have been performed on both in-vitro flow-phantom data and in-vivo human blood flow data. Both data types were acquired under a controlled acquisition protocol developed to minimize the distortion of the color Doppler data and hence to simplify the phase-unwrapping task. In addition to the qualitative assessment of the results, a quantitative assessment approach was developed to measure the success of the results. The results of our new algorithm have been compared on ultrasound data to those from other well-known algorithms, and it outperforms all of them.

Proceedings Article | 21 March 2007 Paper

An interactive 3D user interface for guided bronchoscopy

Indriyati Atmosukarto, Timothy Soper, Robb Glenny, Eric Seibel, Linda Shapiro

Proceedings Volume 6509, 65091G (2007) https://doi.org/10.1117/12.696087

KEYWORDS: Endoscopes, Lung, Particles, Human-machine interfaces, Bronchoscopy, Computed tomography, Particle filters, Navigation systems, 3D displays, Imaging systems

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Proceedings Article | 19 May 2005 Paper

Object and event recognition for aerial surveillance

Yi Li, Indriyati Atmosukarto, Masaharu Kobashi, Jenny Yuen, Linda Shapiro

Proceedings Volume 5781, (2005) https://doi.org/10.1117/12.609109

KEYWORDS: Video, Image segmentation, Video surveillance, Object recognition, Cameras, Roads, Unmanned aerial vehicles, Surveillance, Image classification, Buildings

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Proceedings Article | 19 November 2003 Paper

Detection of neural activity in event-related fMRI using wavelets and dynamic time warping

Hansang Cho, George Ojemann, David Corina, Linda Shapiro

Proceedings Volume 5203, (2003) https://doi.org/10.1117/12.504845

KEYWORDS: Hemodynamics, Functional magnetic resonance imaging, Brain, Wavelets, Signal detection, Interference (communication), Discrete wavelet transforms, Neuroimaging, Distortion, Signal generators

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Proceedings Article | 17 December 1998 Paper

Triangle-inequality-based pruning algorithms with triangle tries

Andrew Berman, Linda Shapiro

Proceedings Volume 3656, (1998) https://doi.org/10.1117/12.333855

KEYWORDS: Distance measurement, Databases, Wavelets, Composites, Sensors, RGB color model, Binary data, Content based image retrieval, Image retrieval, Algorithm development

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Proceedings Article | 15 January 1997 Paper

Efficient image retrieval with multiple distance measures

Andrew Berman, Linda Shapiro

Proceedings Volume 3022, (1997) https://doi.org/10.1117/12.263409

KEYWORDS: Distance measurement, Databases, Image retrieval, Computing systems, Composites, Wavelets, RGB color model, Quantization, Data modeling, Computer science

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Proceedings Article | 23 March 1995 Paper

Implementing multilevel queries in a database environment for vision research

Rex Jakobovits, Linda Shapiro, Steven Tanimoto

Proceedings Volume 2420, (1995) https://doi.org/10.1117/12.205321

KEYWORDS: Data modeling, Databases, Visual process modeling, 3D modeling, C++, Human-machine interfaces, Image processing, Computing systems, Data communications, Safety

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Proceedings Article | 23 March 1995 Paper

Flexible data organization with visualization support for a visual database system

Lara Lewis, Linda Shapiro, Steven Tanimoto

Proceedings Volume 2420, (1995) https://doi.org/10.1117/12.205311

KEYWORDS: Visualization, Databases, Image segmentation, Data modeling, Data storage, Imaging systems, Scientific visualization, Image storage, Visual analytics, Model-based design

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Proceedings Article | 1 June 1992 Paper

Knowledge-based organ identification from CT images

Masaharu Kobashi, Linda Shapiro

Proceedings Volume 1652, (1992) https://doi.org/10.1117/12.59464

KEYWORDS: Computed tomography, Image segmentation, Kidney, Image processing, Liver, Surgery, Medical imaging, Scanners, Spleen, Imaging systems

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Proceedings Article | 30 April 1992 Paper

Proteus: a reconfigurable computational network for computer vision

Robert Haralick, Arun Somani, Craig Wittenbrink, Robert Johnson, Kenneth Cooper, Linda Shapiro, Ihsin Phillips, Jenq Hwang, William Cheung, Yung Yao, Chung-Ho Chen, Larry Yang, Brian Daugherty, Bob Lorbeski, Kent Loving, Tom Miller, Larye Parkins, Steven Soos

Proceedings Volume 1659, (1992) https://doi.org/10.1117/12.58396

KEYWORDS: Image processing, Machine vision, Process control, Telecommunications, Computer vision technology, Signal processing, Control systems, Data processing, Computer architecture, Binary data

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Proceedings Article | 1 April 1992 Paper

Optimal affine-invariant matching: performance characterization

Mauro Costa, Robert Haralick, Linda Shapiro

Proceedings Volume 1662, (1992) https://doi.org/10.1117/12.58489

KEYWORDS: Systems modeling, Affine motion model, Image storage, Solid modeling, Data modeling, Visual process modeling, Computer aided design, Performance modeling, Image processing, Error analysis

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Proceedings Article | 1 January 1990 Paper

Experiments in model-based matching using a relational pyramid representation

Nancy Chu, Linda Shapiro

Proceedings Volume 1293, (1990) https://doi.org/10.1117/12.21074

KEYWORDS: Model-based design, 3D image processing, Feature extraction

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Showing 5 of 18 publications

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